1. Introduction
In recent years, rural entrepreneurial entities have effectively contributed to the development of China’s regional economy, especially its rural economy, by relying on vitality. However, the dominant, backward, and extensive operational models have challenged the sustainability of rural development [1,2]. Environmental pollution issues are particularly prominent [3], and the resulting population reduction, talent loss, and slowdown of economic growth may have lasting social and ecological consequences [4,5]. To overcome this dilemma and encourage more returning talent, especially graduates trained by universities with the intention of returning to their hometowns and actively engaging in green entrepreneurship, the central government issued a strategic document in 2018 called the Opinions on Implementing the Rural Revitalization Strategy [6]. The document clearly states that entrepreneurship promotion actions will be implemented, supporting universities in comprehensively utilizing educational and training resources, innovating talent cultivation models, and cultivating specialized talent for rural revitalization. The basic goals of improving rural ecological environments and building beautiful and livable rural areas will be achieved by 2035. Subsequently, the State Council successively issued a series of policy documents, including the Rural Revitalization Strategic Plan (2018–2022) [7] and the Notice on Further Improving the Employment and Entrepreneurship Work of Youth such as College Graduates [8]. At the same time, based on the goals and requirements of the central government, as well as the development laws of higher education, the Ministry of Education has issued relevant regulations, including the Opinions on Vigorously Promoting Innovation and Entrepreneurship Education in Higher Education Institutions and Autonomous Entrepreneurship Work for University and College Students [9], as well as the Notice on Doing a Good Job in Employment and Entrepreneurship Work for Graduates of 2019 National Ordinary Universities [10], to encourage universities to actively explore the diversified path of cultivating returning entrepreneurial talent, especially those with green intentions. Therefore, cultivating green returnee entrepreneurs has become necessary for universities to comply with current trends, implement rural revitalization strategies effectively, and promote regional and global environmental improvements.
Although the academic community has achieved fruitful results in entrepreneurship education research by covering the research objectives, perspectives, methods, sample characteristics, and model exploration [11,12,13], many shortcomings remain. For example, no specialized research has been conducted on REE and its relationship with environmental sustainability. A sample of university graduates who have received REE has not been analyzed to test the unique or diverse effects of REE. REE has not been linked to or modelled with GREB. Given the diversity and complexity of the influencing factors, constructing a reasonable conceptual model to study their relationship is necessary [14,15]. Therefore, systematic research on models linking REE and GREB must be conducted. This has profound implications for the effectiveness of REE and related factors driving GREB, and ultimately achieving regional and global environmental improvements.
This empirical analysis makes three major contributions to the literature. First, the impact of REE on regional and global environmental improvements is explored for the first time. Second, based on the resource-based view and flow theories, a conceptual model was constructed to link REE with GREB. Third, based on the empirical results, a series of measures was proposed to promote GREB by optimizing REE and institutional support, thereby improving the regional and global environments. In summary, this study provides a beneficial exploration that promotes environmental sustainability and a practical reference for other developing countries to drive GREB effectively.
2. Literature Review
2.1. REE
In academic circles, research on returning home and entrepreneurship has mainly focused on issues related to overseas returnees investing in or starting enterprises [16,17], including their role [18], influencing factors [19], and new issues and solutions [20]. However, in addition to international mobility, population mobility includes forms of domestic mobility such as return behavior due to urbanization [21]. However, research on returning home and starting businesses in rural areas has received little attention. In this study, returnee entrepreneurship refers to the behavior and process of individuals returning to their rural home region to open a business after obtaining professional and/or educational experience in the city [21,22]. Entrepreneurship in rural areas can solve many problems in local development, such as insufficient employment opportunities [23], population reduction [24], capital shortages and outflows [25], closed-mindedness [26], lack of innovation [14], economic stagnation [27], and widening gaps in urban development [28]. However, hidden dangers cannot be underestimated. For example, rural environmental pollution has become a major problem [29,30].
From the perspective of sustainable development strategies, measures such as implementing REE, promoting entrepreneurs with a CE who may participate in returnee entrepreneurship in the future, enhancing the entrepreneurial intentions of green returnees, and implementing their behaviors are necessary. Although scholars have paid close attention to returnee entrepreneurship [21], no relevant studies have been found that specifically examined REE. Therefore, this study considers REE.
2.2. Green Entrepreneurship and GREB
Research has shown that green entrepreneurship and production are inevitable choices for promoting sustainable global development [31]. Green entrepreneurship can effectively alleviate various environmental challenges caused by traditional industries and businesses [32], such as waste and toxic emissions [33], global warming [34], depletion of natural resources [35], and ecological degradation [36]. However, measures must be taken to encourage entrepreneurs to implement green entrepreneurship and realistically achieve environmental improvements [37,38]. To achieve this, support from the education sector, government departments, and other social groups is necessary [15,36], such as the cultivation of knowledge [39], ability [40], ambition [41], and values [42], as well as assistance from policies [43], technology [44], funding [45], and other related services [46]. In recent years, green entrepreneurship education has received widespread attention primarily for research purposes [47], object selection [48], method exploration [49], and effect evaluation [50]. Among these, the exploration of the impact of green entrepreneurship education on environmental awareness and green entrepreneurial intention has been relatively in-depth [15,51]. Currently, effective support methods include green policy [43], business incubators [52], digital technology [53], business models [54], and multipath financing channels [55,56].
Scholars generally believe that providing appropriate education and support to entrepreneurial subjects is extremely important to effectively drive green entrepreneurial behavior and avoid environmental risks and hidden dangers [57,58]. With the continuous deepening of the returnee entrepreneurship process against the background of the Rural Revitalization Strategy, targeted green entrepreneurship education and support have become increasingly urgent. However, no relevant research results were found, suggesting that the driving force of GREB lacks effective guidance from macrotheory and micropractice. Therefore, this study explores, for the first time, the impact of green entrepreneurship education and diversified green entrepreneurship support on the occurrence of GREB in an attempt to break the ice for research in this important subfield.
3. Construction of Conceptual Models
In recent years, the resource-based view and flow theories have been widely applied in entrepreneurship research [15]. Resource-based view theory states that entrepreneurial resources are key to the survival and development of entrepreneurial entities, dominating their competitive advantage, including material, ability, and organizational capital [59,60]. Flow theory is explained as a psychological state that stimulates certain behaviors, such as motivation and intention, which bring great pleasure and enjoyment [61,62]. In college, students acquire entrepreneurial knowledge, skills, and values, which is reflected in entrepreneurial intention and behavior [12,63]. Therefore, this study attempts to expand the comprehensive analysis framework of the resource perspective and flow theory, construct a conceptual model that links REE and GREB, and explore the impact of the model’s factors on environmental sustainability.
3.1. REE and CE
Entrepreneurship education is an effective way of imparting knowledge, skills, and concepts to potential entrepreneurs [11,13]. In recent years, responding to global environmental issues, many universities have continuously improved the status of environmental awareness in education, actively enhanced students’ ecological safety concepts, and focused on increasing their CE [42,51]. Cutting-edge research indicates that entrepreneurship education positively promotes a CE [15]. Similarly, REE may be beneficial for enhancing the CE. Therefore, we assume the following:
REE has a significantly positive impact on CE.
3.2. Role of CE
A CE implies a high level of attention to the environment and a strong intention to improve it [64,65], which directly affects entrepreneurial behavior, including production, sales, and pollution treatment [33,66]. This enhances the entrepreneurs’ social status, reputation, and benefits their enterprises [41,67]. Entrepreneurs with ecological thinking actively develop green projects and seek strong support from various social institutions, including governments, education departments, industry associations, and multinational organizations to initiate and operate green enterprises [38,52,68]. Consequently, relevant social institutions committed to improving environmental ecology have begun to provide and optimize institutional support to help entrepreneurs fulfill their CE [15,64,66]. Institutional support may positively influence entrepreneurs’ CE. Therefore, we assume the following:
CE has a significantly positive impact on institutional support.
Researchers believe that, driven by a sense of social responsibility, entrepreneurs’ CE has a positive impact on environmental ecology [33]. Potential entrepreneurs’ CE is sublimated into internal intentions, which are more common among university students [51,69]. Moreover, university students with high-intensity ecological thinking strengthened their intention to protect their environment and ecology [70]. Research shows that a CE positively affects green entrepreneurship motivation [15]. Therefore, we assume the following:
CE has a significant positive impact on green returnee entrepreneurial intentions.
Entrepreneurs with ecological values take positive actions to prevent environmental damage during their entrepreneurial process [66,67]. Their CE guides them in starting and developing green enterprises, thus promoting the realization of environmental sustainability [41,42]. Therefore, we assume the following:
CE has a significant positive impact on GREB.
3.3. Role of Institutional Support
Researchers believe that sufficient external resources support play a promoting role in stimulating potential entrepreneurs’ enthusiasm, confidence, and preparation [71,72], among which institutional support plays a crucial role [73,74]. Strong institutional support and guarantees are among the most attractive conditions for launching sustainable enterprises and projects [37,68]. These social institutions are generally established and implemented by central or local governments, education departments, industry associations, and some international organizations; the coverage, derivative methods, and specific support paths mainly involve laws and regulations [75,76], policies and norms [32,77], business models and operating funds [78,79], business incubators, and core technologies [35,80]. For example, the institutional support implemented by universities, including financial sponsorship, policy instruments, green project recommendations, and the construction of an encouraging cultural system, has a strong promotional effect on green entrepreneurship behavior [15]. Therefore, we assume the following:
Institutional support has a significant positive impact on GREB.
3.4. Role of Green Returnee Entrepreneurial Intention
Based on the theory of planned behavior [81], intention is one of the most common indicators for predicting entrepreneurial behavior [82,83]. Scholars believe that starting and persisting in a new enterprise is a deliberate act [84] fulfilling inner commitment [85,86]. The results indicate that entrepreneurial behavior is positively and significantly influenced by entrepreneurial intention [12,82]. This functional relationship has also been verified for the intention and behavior of green entrepreneurship [37,87]. Similarly, green returnee entrepreneurial intentions may play a positive role in promoting entrepreneurial behavior. Therefore, we assume the following:
Green returnee entrepreneurial intentions have a significant positive impact on their GREB.
Figure 1 shows the conceptual model tested in this study, where the arrows represent hypothetical relationships between the factors.
4. Methods
4.1. Research Population and Data
The survey targeted new graduates who had received REE during their university years. They came from 13 prefecture-level cities in Jiangsu Province, China, and participated in an online questionnaire. The survey’s title page indicates the background of the investigation, principles of identity confidentiality, precautions for participating, and the right to withdraw from the investigation at any time. After answering the question, “Have you received any form of REE during your university years?” and selecting “Yes”, respondents entered the formal investigation process, while those who chose “No” exited the process.
Relevant data were collected between March and July 2023 using a convenience sampling technique supported by the survey process. Using the Sojump online survey platform, the questionnaire was disseminated through Tencent QQ and WeChat, along with groups therein. In the effective answer stage, 623 responses were received, 358 (57.46%) of which were completed. The data set is presented in Table S1 in the Supplementary Material. Statistical results showed that the majority of respondents were male (n = 297, 82.96%), with the highest number in the age group of 25 years and below (n = 261, 72.91%). Some respondents had a bachelor’s degree (n = 287, 80.17%) or a master’s degree (n = 47, 13.13%).
4.2. Data Measurement
Based on previous achievements of the academic community, the questionnaire was improved after pretesting 30 respondents and consulting three academic experts. The first and second parts included the constructs and demographic scales, respectively. Meanwhile, a seven-point Likert scale was used for the measurement of construct items, with one through seven representing strong disagreement and strong agreement, respectively.
4.2.1. REE
A four-item measurement scale for REE was improved based on the research results on entrepreneurship education by Walter and Block [88], which was used to evaluate the impact of REE on respondents. A sample item is “my school education made me interested in becoming a returnee entrepreneur”. Supplementary Table S2 shows the complete REE measurement scale.
4.2.2. CE
A seven-item scale for CE was adopted from Alcock [89] to evaluate the degree of respondents’ commitment to environmental sustainability. A sample item is “I personally need to change my way of life so that future generations can continue to enjoy a good quality of life and environment”. Table S2 shows the complete measurement scale for CE.
4.2.3. Green Returnee Entrepreneurial Intention
A seven-item scale for green returnee entrepreneurial intention was improved based on the results of Amankwah and Sesen [87] on green entrepreneurship intention, which measured the degree of respondents’ green returnee entrepreneurial intention. Sample items include “I am ready to do anything to be a green returnee entrepreneur”. Table S2 shows the complete measurement scale for the green returnee EIs.
4.2.4. Institutional Support
The four-item scale for institutional support was improved based on the previous research results of Dwivedi et al. [90] and Fox et al. [91] and evaluated the institutional support of the external environment for green returnee entrepreneurship, mainly involving government planning, institutional structure, information, funding, and other aspects. A sample item is, “There are sufficient institutional support structures to assist green returnee Enterprises”. Table S2 presents the integrity measurement scale for institutional support.
4.2.5. GREB
A five-item scale for the GREB was also improved based on previous research by Hameed et al. [15] and Yi [37] to measure the status of individuals taking specific actions to initiate and operate entrepreneurial projects or enterprises. A sample item is “Purchased material, equipment or machinery for the green returnees’ business”. Table S2 lists the integrity measurement scales for the GREB.
4.3. Methodology
Covariance-based structural equation models (CB-SEM) [15,92] and partial least squares structural equation modeling (PLS-SEM) [93,94] are often used to test hypotheses and interaction relationships between factors, particularly in entrepreneurship research. Compared with CB-SEM, PLS-SEM has the advantages of non-normal data distribution and small sample size requirements [95,96], which better meet the evaluation needs of the realistic characteristics of this study’s sample. Accordingly, following a more appropriate principle, this study used PLS-SEM and SmartPLS 4 software to verify the measurement and structural models separately using a two-stage analysis method [97].
5. Results and Discussion
5.1. Significance Estimation of the Measurement and Structural Models
First, after clarifying that all observable indicators were reflective, their effectiveness was screened using correlation and partial correlation analyses to construct an initial structural equation.
Second, the PLS algorithm was used to estimate the internal consistency reliability, convergent validity, and discriminant validity of the measurement model [98]. Cronbach’s alpha (CA) and composite reliability (CR) are commonly used indicators of internal consistency. The CA value should be greater than 0.7, whereas the CR value should be greater than 0.6 (acceptable) or 0.7 (satisfactory). The outer loading coefficient and average variance extracted (AVE) are commonly used test indicators of convergence validity and should be greater than 0.7 and 0.5, respectively. The Fornell–Larcker criterion is a commonly used evaluation indicator of discriminant validity, and the square root of the AVE must be greater than the correlation coefficient between latent variables [99]. The estimated results (Table 1 and Table 2) show that the reliability and validity of the measurement model were ideal.
Finally, based on the bootstrapping method, a significance test was conducted on the interaction between the factors in the structural model [100,101]. The results are presented in Table 3 and Figure 2 and Figure 3.
5.2. Interaction Mechanism between Various Factors in the Conceptual Model
The evaluation results (Figure 2 and Figure 3 and Table 3) show that the impact of REE on CE is positively significant, with a path coefficient of 0.527, indicating that H1 is valid. This finding suggests that REE is effective in stimulating student commitment to environmental protection. This commitment may have a positive impact on regional and global ecological environments on a larger scale [33,64,66].
Second, the impact of CE on institutional support was positive and significant, with a path coefficient of 0.541, indicating that H2 is valid. This suggests that social institutions committed to improving the environment are positively influenced by students’ CE and that they are willing and able to provide institutional support to create conditions for students to fulfill these commitments [64,66].
Third, green returnee entrepreneurial intentions are positively and significantly influenced by their CE, with a path coefficient of 0.542, thus supporting H3. This indicates that green returnee entrepreneurship intentions are promoted and strengthened by their CE. This intention demonstrates a strong ecological perspective that leads students to make important and lasting contributions to further improve environmental ecology [42,51].
Fourth, CE did not have a significant positive impact on GREB, with a path coefficient of 0.068, indicating that H4 is invalid. This indicates that the direct impact of CE on students’ GREB is weak, meaning that the responsibility generated by CE is not strong enough to encourage students to engage in green returnee entrepreneurship directly.
Fifth, GREB was positively and significantly influenced by institutional support, with a path coefficient of 0.396, supporting H5. Strong institutional support effectively ensures the initiation and development of green returnee enterprises or projects, meaning that support paths and methods, including laws, policies, and funds are beneficial for promoting the implementation of GREB.
Sixth, green returnee entrepreneurial intention has a positively significant impact on their entrepreneurial behavior, with a path coefficient of 0.368, supporting H6. This means that initiating green returnee enterprises or projects is deliberate, reflecting that ecological values can inspire individuals to take positive action to achieve their commitments [41,102].
In addition, from the perspective of mediating effects among factors, except for the REE→CE→GREB path, all other mediation and serial mediation paths have a positively significant effect. In other words, REE, CE, institutional support, and green returnee entrepreneurial intention have direct or indirect promotional effects on GREB.
6. Conclusions and Policy Implication
Based on the interaction results, REE had a high impact on student CE. By directly and effectively shaping student CE, universities play a key role in indirectly initiating and promoting regional and global environmental improvement. Universities are known to have a significant effect on students and their values [42,51]. Based on this, universities should strengthen and deepen education on returnee entrepreneurship from the perspective of global, national, and regional environmental protection strategies with a focus on effectively shaping student CE through courses, practical training, and value guidance. Universities shoulder a significant responsibility for achieving environmental sustainability through talent cultivation paths.
Although a CE did not have a direct or significant impact on GREB, they did have a significant indirect impact through institutional support and returnees’ intentions. These results indicate that triggering GREB may require the intervention of other factors such as resources and motivation. Therefore, government agencies, education departments, and other social organizations should incorporate other intermediary factors, such as external resource supply and student intention guidance, to provide the indispensable conditions for students to implement their CE.
The results for the constructed relationships show that institutional support has a positive and significant impact on GREB. Therefore, institutional support should be comprehensive [37,68]. Guided by the national Rural Revitalization Strategy aimed at achieving sustainable rural development, necessary and effective institutional support must be provided from the central government to the local, from government to industry, and from the domestic to the global level to achieve diversified resource guarantees. However, from a practical perspective, targeted support actions and forces are insufficient, as are institutional support at different levels, dimensions, methods, and paths [14,29,103]. Therefore, based on the resource-based view theory, social entities with the intention and ability to provide support should be further manifested, which has profound significance for the stimulation of student behavior and promoting environmental improvement.
The evaluation results show that green returnee entrepreneurial intentions have a positive and significant impact on their entrepreneurial behavior. Thus, from the perspective of flow theory, certain positive psychological states can be effectively stimulated [61,62]. The intention triggered by a CE leads to the occurrence of specific behaviors. Therefore, for any driving force behind green returnee entrepreneurship, measures should be implemented to shape students’ entrepreneurial intentions. Students must be provided with positive and lasting experiences, including a sense of achievement, responsibility, professionalism, longing, excitement, and happiness, to stimulate their real-life behaviors effectively.
In addition, from the overall evaluation process of the conceptual model, both sets of local serial-mediation paths have positive and significant effects, including REE→CE→GREI→GREB and REE→CE→IS→GREB. This implies that regional and global environmental protection can be achieved through the collaboration of multiple social entities, including central and local governments, education departments, financial institutions, industry associations, and international organizations. Among these, educational departments, represented by universities, play a leading role. REE implementation can positively affect students’ values, intentions, and institutional support at different levels, thereby promoting GREB. In conclusion, the education sector can adopt broader and more deeply integrated measures from global and national strategic perspectives to drive students to engage in green returnee entrepreneurship through the collaborative efforts of multiple entities, thereby contributing to regional and global environmental protection.
7. Contributions, Limitations, and Future Research
This is the first study to discuss the impact of REE on regional and global environmental improvements. Based on the resource-based view and flow theories, a serial mediation model was constructed for the first time to link REE to GREB. Based on the empirical results, a series of measures are proposed to drive green returnee entrepreneurial behavior by optimizing education and institutional support to achieve environmental improvement.
Although this study has some achievements, it has several limitations. First, in addition to university students, the objects of the REE may also include migrant workers, entrepreneurs, the unemployed, and other social groups; however, this study did not explore this aspect. A larger study area should be considered in the future. Second, from a certain point of view, REE may be considered a form of institutional support. This study did not discuss this perspective but directly evaluated the relationship between the two. In the future, we plan to study this topic in greater detail. Third, the impact intensity of the different institutional support subjects differed; however, this study did not distinguish between them. Future studies should conduct detailed analyses of the differences in support from governments, financial institutions, universities, and international organizations. Fourth, the mediating factors between REE and behavior are not limited to the three factors involved in the model. Other factors are likely to have more significant mediating effects. More in-depth identification and testing of the possible mediating factors will be conducted in future studies. Fifth, given the community nature of environmental protection, in addition to universities, REE may also widely exist at other levels of the education system, such as secondary schools. This means that the main body and scope of implementing environmental protection strategies may need to be expanded further; however, this study did not explore them. In the future, we plan to conduct research based on higher station positions and broader perspectives.
Conceptualization, Q.Y. and D.W.; data curation, Q.Y. and Y.W.; methodology, Q.Y.; software, Q.Y.; writing of the original draft, Q.Y.; review and editing, D.W. and Y.W.; visualization, Y.W.; supervision, D.W. and Y.W. All authors have read and agreed to the published version of the manuscript.
This study was conducted in accordance with the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board of Huaiyin Normal University.
Informed consent was obtained from all participants involved in the study.
The data presented in this study are available in
The authors declare no conflict of interest.
Footnotes
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Outer loading coefficient, CA, CR, and AVE values.
| Construct | Abbreviation | Variable | Outer Loading Coefficient | CA | CR | AVE |
|---|---|---|---|---|---|---|
| Returnee entrepreneurship education | REE | REE1 | 0.890 | 0.892 | 0.898 | 0.756 |
| REE2 | 0.885 | |||||
| REE3 | 0.847 | |||||
| REE4 | 0.855 | |||||
| Commitment to the environment | CE | CE1 | 0.841 | 0.931 | 0.932 | 0.708 |
| CE2 | 0.889 | |||||
| CE3 | 0.820 | |||||
| CE4 | 0.839 | |||||
| CE5 | 0.833 | |||||
| CE6 | 0.827 | |||||
| CE7 | 0.837 | |||||
| Green returnee entrepreneurial intention | GREI | GREI1 | 0.765 | 0.893 | 0.896 | 0.611 |
| GREI2 | 0.871 | |||||
| GREI3 | 0.784 | |||||
| GREI4 | 0.823 | |||||
| GREI5 | 0.750 | |||||
| GREI6 | 0.703 | |||||
| GREI7 | 0.765 | |||||
| Institutional support | IS | IS1 | 0.873 | 0.888 | 0.889 | 0.749 |
| IS2 | 0.863 | |||||
| IS3 | 0.854 | |||||
| IS4 | 0.872 | |||||
| Green returnee entrepreneurial behavior | GREB | GREB1 | 0.819 | 0.905 | 0.907 | 0.725 |
| GREB2 | 0.878 | |||||
| GREB3 | 0.863 | |||||
| GREB4 | 0.857 | |||||
| GREB5 | 0.840 |
Discriminant validity.
| Variable | CE | GREB | GREI | IS | REE |
|---|---|---|---|---|---|
| CE | 0.841 | ||||
| GREB | 0.482 | 0.852 | |||
| GREI | 0.542 | 0.530 | 0.782 | ||
| IS | 0.541 | 0.550 | 0.318 | 0.865 | |
| REE | 0.527 | 0.287 | 0.253 | 0.255 | 0.869 |
Note: Values located diagonally represent the square roots of the AVE values, whereas the other values represent correlations between the latent variables.
Structural path estimation.
| Influence Path | Hypothesis | Path Coefficients | Standard Deviation | T-Values | p-Values | Significance |
|---|---|---|---|---|---|---|
| REE→CE | H1 | 0.527 | 0.038 | 13.922 | 0.000 | *** |
| CE→IS | H2 | 0.541 | 0.040 | 13.677 | 0.000 | *** |
| CE→GREI | H3 | 0.542 | 0.039 | 13.903 | 0.000 | *** |
| CE→GREB | H4 | 0.068 | 0.054 | 1.258 | 0.208 | – |
| IS→GREB | H5 | 0.396 | 0.047 | 8.513 | 0.000 | *** |
| GREI→GREB | H6 | 0.368 | 0.047 | 7.859 | 0.000 | *** |
| REE→CE→GREB | – | 0.036 | 0.029 | 1.247 | 0.213 | – |
| REE→CE→IS | – | 0.285 | 0.030 | 9.364 | 0.000 | *** |
| CE→IS→GREB | – | 0.214 | 0.030 | 7.148 | 0.000 | *** |
| REE→CE→IS→GREB | – | 0.113 | 0.018 | 6.118 | 0.000 | *** |
| REE→CE→GREI | – | 0.286 | 0.031 | 9.282 | 0.000 | *** |
| CE→GREI→GREB | – | 0.199 | 0.029 | 6.925 | 0.000 | *** |
| REE→CE→GREI→GREB | – | 0.105 | 0.018 | 5.899 | 0.000 | *** |
Note: *** indicates the 0.1% significance level.
Supplementary Materials
The following supporting information can be downloaded at:
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1 Business School, Huaiyin Normal University, Huai’an 223001, China
2 School of Economics and Management, China University of Mining and Technology, Xuzhou 221116, China;